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      Transcriptomic analysis of cork during seasonal growth highlights regulatory and developmental processes from phellogen to phellem formation

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          Abstract

          The phellogen or cork cambium stem cells that divide periclinally and outwardly specify phellem or cork. Despite the vital importance of phellem in protecting the radially-growing plant organs and wounded tissues, practically only the suberin biosynthetic process has been studied molecularly so far. Since cork oak ( Quercus suber) phellogen is seasonally activated and its proliferation and specification to phellem cells is a continuous developmental process, the differentially expressed genes during the cork seasonal growth served us to identify molecular processes embracing from phellogen to mature differentiated phellem cell. At the beginning of cork growth (April), cell cycle regulation, meristem proliferation and maintenance and processes triggering cell differentiation were upregulated, showing an enrichment of phellogenic cells from which phellem cells are specified. Instead, at maximum (June) and advanced (July) cork growth, metabolic processes paralleling the phellem cell chemical composition, such as the biosynthesis of suberin, lignin, triterpenes and soluble aromatic compounds, were upregulated. Particularly in July, polysaccharides- and lignin-related secondary cell wall processes presented a maximal expression, indicating a cell wall reinforcement in the later stages of cork formation, presumably related with the initiation of latecork development. The putative function of relevant genes identified are discussed in the context of phellem ontogeny.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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              STAR: ultrafast universal RNA-seq aligner.

              Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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                Author and article information

                Contributors
                olga.serra@udg.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                8 June 2021
                8 June 2021
                2021
                : 11
                : 12053
                Affiliations
                GRID grid.5319.e, ISNI 0000 0001 2179 7512, Laboratori del Suro, Departament de Biologia, , Universitat de Girona, ; Campus Montilivi, 17003 Girona, Spain
                Article
                90938
                10.1038/s41598-021-90938-5
                8187341
                286c92c9-918c-4976-8a44-dd943e0e0789
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 4 January 2021
                : 19 May 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100008722, Universitat de Girona;
                Funded by: FundRef http://dx.doi.org/10.13039/501100003329, Ministerio de Economía y Competitividad;
                Award ID: AGL2012-36725
                Award ID: AGL2012-36725
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100004837, Ministerio de Ciencia e Innovación;
                Award ID: PID2019-110330GB-C21
                Award ID: PID2019-110330GB-C21
                Award Recipient :
                Funded by: The European Regional Development Fund (ERDF)
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                plant development,cell fate,plant stem cell
                Uncategorized
                plant development, cell fate, plant stem cell

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